This workflow follows the Chainllm → Gmail recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
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{
"name": "GenAI & Agentic AI Daily Career Briefing",
"nodes": [
{
"parameters": {
"rule": {
"interval": [
{
"triggerAtHour": 8
}
]
}
},
"id": "90351921-f0b9-4345-96ff-183ce9a02bda",
"name": "Daily Trigger - News",
"type": "n8n-nodes-base.scheduleTrigger",
"typeVersion": 1.3,
"position": [
224,
208
]
},
{
"parameters": {
"url": "https://news.google.com/rss/search?q=%22agentic+AI%22+OR+%22generative+AI%22+OR+%22AI+agent%22+OR+%22AI+tool%22+OR+%22AI+regulation%22+OR+%22AI+policy%22&hl=en-US&gl=US&ceid=US:en",
"options": {}
},
"id": "c2def01e-6852-4a18-9a6a-835f557a6836",
"name": "Fetch Google News RSS",
"type": "n8n-nodes-base.rssFeedRead",
"typeVersion": 1.2,
"position": [
448,
208
]
},
{
"parameters": {},
"id": "dd7d4b7c-115b-4269-b373-f66bf0748594",
"name": "Combine News Sources",
"type": "n8n-nodes-base.merge",
"typeVersion": 3.2,
"position": [
672,
112
]
},
{
"parameters": {
"rule": {
"interval": [
{
"triggerAtHour": 8
}
]
}
},
"id": "eed54d77-5620-4a34-a192-5ac422c77a36",
"name": "Daily Trigger - HN",
"type": "n8n-nodes-base.scheduleTrigger",
"typeVersion": 1.3,
"position": [
0,
16
]
},
{
"parameters": {
"url": "https://hn.algolia.com/api/v1/search_by_date?query=AI%20agent&tags=story&hitsPerPage=20",
"options": {}
},
"id": "5cbde002-9c84-4641-a6cb-8c7b39381aba",
"name": "Fetch Hacker News",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.4,
"position": [
224,
16
]
},
{
"parameters": {
"fieldToSplitOut": "hits",
"options": {
"destinationFieldName": "story"
}
},
"id": "a8179141-9c0e-48c0-be64-e09b3d28d6ad",
"name": "Split HN Hits",
"type": "n8n-nodes-base.splitOut",
"typeVersion": 1,
"position": [
448,
16
]
},
{
"parameters": {
"jsCode": "\nconst seen = $getWorkflowStaticData('global');\nif (!seen.sentLinks) seen.sentLinks = [];\n\nconst cutoffMs = Date.now() - 24 * 60 * 60 * 1000;\nconst normalized = [];\n\nfor (const item of $input.all()) {\n const j = item.json;\n let title, link, publishedMs;\n\n if (j.story) {\n title = j.story.title;\n link = j.story.url || ('https://news.ycombinator.com/item?id=' + j.story.objectID);\n publishedMs = j.story.created_at ? new Date(j.story.created_at).getTime() : Date.now();\n } else {\n title = j.title;\n link = j.link;\n publishedMs = j.isoDate ? new Date(j.isoDate).getTime() : (j.pubDate ? new Date(j.pubDate).getTime() : Date.now());\n }\n\n if (!title || !link) continue;\n if (seen.sentLinks.includes(link)) continue;\n if (publishedMs < cutoffMs) continue;\n\n normalized.push({ title, link, publishedMs });\n seen.sentLinks.push(link);\n}\n\nif (seen.sentLinks.length > 500) {\n seen.sentLinks = seen.sentLinks.slice(-500);\n}\n\nnormalized.sort((a, b) => b.publishedMs - a.publishedMs);\nconst top = normalized.slice(0, 15);\n\nconst articlesText = top.map((a, i) => (i + 1) + '. ' + a.title + ' - ' + a.link).join('\\n');\n\nreturn [{ json: { articlesText: articlesText, count: top.length } }];\n"
},
"id": "3e34c2b6-dbeb-4282-922d-43ceb8be39e4",
"name": "Dedupe, Filter & Build Digest",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
896,
112
]
},
{
"parameters": {
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "strict",
"version": 1
},
"conditions": [
{
"leftValue": "={{ $json.count }}",
"operator": {
"type": "number",
"operation": "gt"
},
"rightValue": 0
}
],
"combinator": "and"
},
"options": {}
},
"id": "61d1b7b0-d7d8-4988-8e90-a9097f36f854",
"name": "Has New Items?",
"type": "n8n-nodes-base.filter",
"typeVersion": 2.3,
"position": [
1120,
112
]
},
{
"parameters": {
"promptType": "define",
"text": "=You are an expert AI Career Analyst writing a daily GenAI/Agentic AI briefing. \nAnalyze the following headlines and extract a structured JSON object.\nYou MUST output ONLY a valid JSON object. Do not include markdown formatting, backticks, or text outside the JSON.\n\nThe JSON must match this exact schema:\n{\n \"sentiment\": {\n \"score\": \"Bullish, Bearish, or Neutral\",\n \"reason\": \"1 sentence explanation of the market mood\"\n },\n \"top_news\": [\n {\"headline\": \"title\", \"impact\": \"1-2 lines on why it matters\"}\n ],\n \"models_tools\": [\n \"model/tool name 1\", \"model/tool name 2\"\n ],\n \"skills\": [\n {\"skill\": \"Skill Name\", \"reason\": \"Why it's relevant this week\"}\n ],\n \"industry_impact\": \"2-3 sentences on how this affects engineering roles\"\n}\n\nHeadlines:\n{{ $json.articlesText }}",
"batching": {}
},
"id": "5744fbf8-0ed5-4c50-8cc2-04039fa92023",
"name": "Build Career Briefing",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"typeVersion": 1.9,
"position": [
1344,
112
]
},
{
"parameters": {
"modelName": "models/gemini-3.1-flash-lite",
"options": {}
},
"id": "284d729d-e67e-48d8-b6f7-223021bbfb94",
"name": "Gemini Model",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"typeVersion": 1.1,
"position": [
1424,
336
],
"notesInFlow": true,
"notes": "THIS IS WORKFLOW FOR LATEST NEWS"
},
{
"parameters": {
"jsCode": "\ntry {\n let parsed = $input.first().json.text;\n if (typeof parsed === 'string') {\n // Strip markdown JSON wrappers if the LLM leaked them\n parsed = parsed.replace(/^```json/, '').replace(/```$/, '').trim();\n parsed = JSON.parse(parsed);\n }\n \n let html = `<div style=\"font-family: sans-serif; max-width: 600px; margin: 0 auto; color: #333;\">`;\n \n // Header & Sentiment\n html += `<h2 style=\"color: #2c3e50; border-bottom: 2px solid #3498db; padding-bottom: 5px;\">Market Sentiment: ${parsed.sentiment.score}</h2>`;\n html += `<p style=\"font-style: italic; color: #555;\">${parsed.sentiment.reason}</p>`;\n \n // Top News\n html += `<h3 style=\"color: #2980b9;\">\ud83d\udd25 Top News Today</h3><ul>`;\n for (const item of parsed.top_news) {\n html += `<li style=\"margin-bottom: 10px;\"><strong>${item.headline}</strong><br><span style=\"font-size: 0.9em; color: #666;\">${item.impact}</span></li>`;\n }\n html += `</ul>`;\n \n // Models & Tools\n html += `<h3 style=\"color: #8e44ad;\">\ud83e\udd16 New Models & Tools</h3><ul>`;\n if (parsed.models_tools && parsed.models_tools.length > 0) {\n for (const tool of parsed.models_tools) {\n html += `<li>${tool}</li>`;\n }\n } else {\n html += `<li>No major releases in today's headlines.</li>`;\n }\n html += `</ul>`;\n \n // Skills\n html += `<h3 style=\"color: #27ae60;\">\ud83d\udee0\ufe0f Skills to Improve</h3><ul>`;\n for (const skill of parsed.skills) {\n html += `<li><strong>${skill.skill}:</strong> ${skill.reason}</li>`;\n }\n html += `</ul>`;\n \n // Impact\n html += `<h3 style=\"color: #d35400;\">\ud83d\udcbc Industry Impact</h3>`;\n html += `<p>${parsed.industry_impact}</p>`;\n \n html += `</div>`;\n \n return [{ json: { htmlEmail: html } }];\n} catch (e) {\n return [{ json: { htmlEmail: \"<p>Error parsing AI Output. Raw text:</p><pre>\" + $input.first().json.text + \"</pre>\" } }];\n}\n"
},
"id": "7626ef91-1234-4567-8901-abcdef123456",
"name": "Format HTML Email",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
1550,
112
]
},
{
"parameters": {
"sendTo": "YOUR_EMAIL@gmail.com",
"subject": "=GenAI & Agentic AI Daily Career Briefing - {{ $now.toFormat(\"MMMM d, yyyy\") }}",
"message": "={{ $json.htmlEmail }}",
"options": {
"appendAttribution": false
}
},
"id": "794bc71a-84df-4948-988d-8fb14732149b",
"name": "Send Email Digest",
"type": "n8n-nodes-base.gmail",
"typeVersion": 2.2,
"position": [
1800,
112
]
}
],
"connections": {
"Daily Trigger - News": {
"main": [
[
{
"node": "Fetch Google News RSS",
"type": "main",
"index": 0
}
]
]
},
"Fetch Google News RSS": {
"main": [
[
{
"node": "Combine News Sources",
"type": "main",
"index": 0
}
]
]
},
"Combine News Sources": {
"main": [
[
{
"node": "Dedupe, Filter & Build Digest",
"type": "main",
"index": 0
}
]
]
},
"Daily Trigger - HN": {
"main": [
[
{
"node": "Fetch Hacker News",
"type": "main",
"index": 0
}
]
]
},
"Fetch Hacker News": {
"main": [
[
{
"node": "Split HN Hits",
"type": "main",
"index": 0
}
]
]
},
"Split HN Hits": {
"main": [
[
{
"node": "Combine News Sources",
"type": "main",
"index": 1
}
]
]
},
"Dedupe, Filter & Build Digest": {
"main": [
[
{
"node": "Has New Items?",
"type": "main",
"index": 0
}
]
]
},
"Has New Items?": {
"main": [
[
{
"node": "Build Career Briefing",
"type": "main",
"index": 0
}
]
]
},
"Build Career Briefing": {
"main": [
[
{
"node": "Format HTML Email",
"type": "main",
"index": 0
}
]
]
},
"Gemini Model": {
"ai_languageModel": [
[
{
"node": "Build Career Briefing",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Format HTML Email": {
"main": [
[
{
"node": "Send Email Digest",
"type": "main",
"index": 0
}
]
]
}
},
"active": false,
"settings": {
"executionOrder": "v1"
}
}
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About this workflow
GenAI & Agentic AI Daily Career Briefing. Uses rssFeedRead, httpRequest, chainLlm, lmChatGoogleGemini. Scheduled trigger; 12 nodes.
Source: https://github.com/sainathgoud1229/gen-ai-news/blob/main/genai-daily-career-briefing.json — original creator credit. Request a take-down →
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